Prospective Assessment of Mood and Quality of Life in Cushing Syndrome Before and After Biochemical Control

Abstract

Context

Cushing’s syndrome (CS) impairs quality of life (QoL) and mood. Prospective real-life data on posttreatment recovery and predictors of improvement are limited.

Objectives

Evaluate changes in QoL, depression, and anxiety in patients with CS, before and after biochemical control, and identify predictors of clinically meaningful improvement.

Design and Setting

Prospective observational study at a tertiary center.

Patients

Sixty-seven patients with endogenous CS (60 pituitary, 7 adrenal) were assessed with active disease and again after achieving biochemical control through surgery and/or medication.

Outcomes

Patient-reported outcomes included CushingQoL, Beck Depression Inventory-II (BDI-II), and State-Trait Anxiety Inventory (STAI).

Results

Mean and longest follow-up was 2.3 and 11.5 years, respectively. Treatment led to improvements in mean scores across all domains (QoL: +18.2 ± 20.9, BDI-II: −6.8 ± 8.6, STAI-State: −9.6 ± 12.5, STAI-Trait: −8.6 ± 12.6; all P < .001). However, a minimal important difference was achieved in 64.6% for QoL, 67.9% for BDI-II, and 53.2% and 52.8% for STAI subscales. After multivariable analysis, QoL improvements were predicted by lower baseline body mass index, pretreatment symptoms ❤ years, postoperative hydrocortisone replacement >6 months, and normal follow-up late-night salivary cortisol (LNSC). Depression improvements were predicted by symptoms ❤ years, normal follow-up LNSC, and surgical treatment. Anxiety improvements were predicted by younger age and >6 months postoperative hydrocortisone. Depression improved more gradually than QoL and anxiety.

Conclusion

Although effective treatment improves mood and QoL in CS, clinically meaningful recovery is variable and incomplete for some patients. Our findings highlight the need to limit diagnostic delay and provide comprehensive posttreatment care that includes normalization of cortisol circadian rhythm.

Endogenous Cushing’s syndrome (CS) is a rare disorder characterized by chronic cortisol excess, most commonly due to an ACTH-secreting pituitary tumor [Cushing disease (CD)], followed by a cortisol-secreting adrenal adenoma and ectopic ACTH production due to a nonpituitary tumor (1). CS is associated with multiple comorbidities including diabetes, obesity, hypertension, immune suppression, osteoporosis, and cardiovascular disease, among others (2). Apart from these, patients face a spectrum of neuropsychiatric disturbances including depression, anxiety, mania, sleep disorders, and even psychosis. These comorbidities significantly disturb quality of life (QoL) and may persist long after treatment (3-7).

As with many rare diseases, CS remains incompletely understood, and patients experience impaired disease perception, information gaps, and isolation. In this context, patient-reported outcomes (PROs) have become useful instruments to clarify these gaps and guide patient-centered care. Disease-specific tools (CushingQoL, Tuebingen CD-25) and generic mood scales (Beck Depression Inventory, State-Trait Anxiety Inventory [STAI; including State (STAI-S) and Trait (STAI-T), Hospital Anxiety and Depression Scale] have established impairments in QoL and mood both during active disease and in remission (48-11).

Although improvements are noted with treatment, recovery does not seem to be complete. Studies have reported persistently reduced QoL compared to the general population and the presence of depressive symptoms even 12 months postoperatively (49). Findings regarding anxiety are less consistent: while some studies did not support the increased prevalence of anxiety in patients with active CS compared to the general population (12), others reported higher anxiety traits among patients with CS (during active disease and in remission) (1314) with steady improvement at 6- and 12-month follow-up (15). Clinical trials with adrenal steroidogenesis inhibitors or pasireotide demonstrated that effective biochemical control can improve QoL and depression (16-18). However, it is unclear whether these improvements are clinically significant and if patients achieve normal QoL and depression scores.

The role of PROs in assessing recovery during the treatment journey of patients with CS has not been clearly established, and QoL and mood trajectories remain unclear, largely due to small samples, limited follow-up, and cross-sectional designs. Among available prospective studies using PROs in CS, only 3 (2 evaluating pasireotide and 1 osilodrostat) reported the proportion of patients who met the minimal important difference (MID), which is the score change reflecting a clinically meaningful improvement (17-19), while others have only reported statistically significant changes in mean score, an important but possibly less clinically relevant outcome (20-22). Real-world clinical management adds further complexity: postoperative glucocorticoid replacement, potential glucocorticoid-withdrawal symptoms, and 20% to 30% recurrence rates after initial surgical “cure” all suggest that, for many patients, recovery may follow a nonlinear course. To date, no clinical practice prospective study has systematically assessed QoL and mood across multiple timepoints, compared surgical and medical strategies within a single cohort, and limited inclusion to patients who achieved biochemical remission or control for at least 6 months. Therefore, the aims of this study were to evaluate changes in QoL, depression, and anxiety in a clinical practice cohort of patients with CS before and over time after biochemical control, report achievement rates of MID, and identify predictors of clinically meaningful improvement.

Methods

Study Design

This study includes prospective data from patients enrolled in an ongoing observational cohort study, which since 2017 enrolls patients with endogenous CS at Memorial Sloan Kettering Cancer Center (MSKCC) [prior to 2017, enrollment took place at Mount Sinai (2012-2017)]. In this protocol, CS patients being treated at the MSKCC Pituitary and Skull Base Tumor Center are enrolled at any point in their treatment journey and prospectively followed over time after surgical, medical, and/or radiation treatment. At each study visit, a detailed medical history and biochemical and clinical data are collected according to standard of care. Patients also complete validated psychological and QoL assessments.

The current analysis includes a cohort of 67 patients with CS: 60 with pituitary and 7 with adrenal CS. Each patient completed a baseline (active disease) visit and at least 1 follow-up visit after achieving surgical remission or endocrine control due to medical therapy.

From the total of 67 patients, we analyzed 73 distinct baseline-to-follow-up case pairs. Six patients experienced recurrence after surgery or were inadequately controlled while on medical therapy after their initial follow-up visit and underwent a subsequent change in treatment strategy. These instances were treated as separate case pairs when needed, enabling comparison of different treatment approaches. When analyzing for a single follow-up, visits were grouped by time: group 1 (G1): 6 months, group 2 (G2): 12-18 months, and group 3 (G3): 24 or more months posttreatment. Each patient contributed to 1 or multiple groups based on the number of their study visits. For patients with multiple visits receiving different treatments throughout the current study, each follow-up visit was categorized based on time since the most recent intervention to ensure that we assessed outcomes according to the duration of biochemical control. For patients who underwent surgery, the follow-up interval was calculated from the date of surgery; for those on medical therapy, it was calculated from the start of medication. In the subanalysis comparing treatment- or demographic-related score changes, the most recent available follow-up was used in each case. At each visit patients completed at least 1 of the following: Cushing QoL, Beck Depression Inventory-II (BDI-II), or STAI-S and STAI-T.

For multiple follow-up visits during remission or treatment, 28 patients were evaluated. For this subgroup, we examined their whole trajectory over time. We then stratified this subgroup by total follow-up duration (<2 years vs ≥2 years) and assessed for significant differences between these 2 categories where applicable.

For the baseline visit, ACTH-dependent pituitary and ACTH-independent adrenal Cushing’s was confirmed according to Endocrine Society guidelines (23). Surgical remission was defined as postoperative serum cortisol <5 μg/dL (<138 nmol/L) and requirement of glucocorticoid replacement, according to the Endocrine Society’s guidelines and the Pituitary Society’s recent consensus statement (2425). For patients managed medically, endocrine control was defined as normalization of 24-hour urinary free cortisol (UFC) and based on clinical review and assessment by E.B.G.

The study was approved by the institutional review board at MSKCC. All subjects gave written informed consent before participation.

Outcome Measurements

Cushing QoL

The Cushing QoL is a validated disease-specific questionnaire consisting of 12 questions on a 5-point scale ranging from “always” to “never” (for 10 questions) or “very much” to “not at all” (for 2 questions). Total score ranges from 12 to 60. This is converted to a 0 to 100 scale, with 0 indicating the worst and 100 the best QoL. It evaluates physical and psychological issues and can also be scored through these 2 distinct subscales. MID is defined as an increase of ≥10.1 (26).

BDI-II

The BDI-II is a validated 21-item patient-reported questionnaire. Patients self-rate each item on a scale from 0 to 3 based on how they were feeling during the past 2 weeks. Total score ranges from 0 (best) to 63 (worst); scores from 0 to 13 indicate no or minimal depression; 14 to 19, mild depression; 20 to 28, moderate depression; and 29 to 63, severe depression. MID is defined as a 20% reduction from baseline score (2728).

STAI

The STAI is an instrument with 2 subscales: State anxiety (STAI-S), which reflects the present moment, and Trait anxiety (STAI-T), which assesses a stable tendency toward anxiety. Both subscales consist of 20 items scored from 0 to 3. Total scores range from 0 to 60, with higher scores indicating greater anxiety. Prior studies suggest a change of 0.5× SDs—or approximately 5 to 10 points—as a reasonable threshold for MID. In our study, we defined the MID at 7 points, based on observed SD of change at 12.5 for STAI-S and 12.6 for STAI-T (29).

In this study, all score changes from baseline to follow-up were reported as positive values to uniformly represent improvement across measures. For BDI-II and STAI where higher scores indicate worse outcomes, the direction of change was inverted for consistency.

Hormone Assays

Hormone testing was performed at either the MSKCC clinical laboratory or external laboratories (Quest Diagnostics, Labcorp, Mayo Clinic Laboratories). Plasma ACTH was measured using Tosoh immunoassay [RRID:AB_2783633; normal range (NR): 7.4-64.3 pg/mL (1.6-14.2 pmol/L); MSKCC or 6 to 50 pg/mL (1.3-11.0 pmol/L); QuestDiagnostics] or electrochemiluminescence immunoassay [RRID:AB_3678556; NR: 7.2-63.3 pg/mL (1.6-13.9 pmol/L); LabCorp, Mayo Clinic Laboratories]. Serum cortisol was measured via either immunoassay [RRID:AB_2802133; NR: 4-22 µg/dL (110-607 nmol/L); QuestDiagnostics or 7-25 µg/dL (193-690 nmol/L); Mayo Clinic Laboratories], electrochemiluminescence immunoassay [RRID:AB_2802131; NR: 6.2-19.4 µg/dL; (171-535 nmol/L); LabCorp], or liquid chromatography–tandem mass spectrometry [LC-MS/MS; NR: 5-25 µg/dL (138-690 nmol/L)]. UFC was measured using LC-MS/MS [NR: 3.5-45 µg/24 hours (9.7-124 nmol/24 hours); MSKCC, Mayo Clinic Laboratories or 3.0 to 50 µg/24 hours (8.3-138 nmol/24 hours); Quest Diagnostics, LabCorp]. Late-night salivary cortisol (LNSC) was assessed via LC-MS/MS [NR: ≤ 0.09 µg/dL (2.5 nmol/L); QuestDiagnostics, LabCorp or <100 ng/dL (27.6 nmol/L); MSKCC, Mayo Clinic Laboratories]. LNSC values were analyzed categorically (normal vs abnormal), and patients were asked to provide 2 LNSC samples on separate evenings. Abnormal LNSC was defined as at least 1 value above the upper limit of normal for the assigned laboratory.

Comorbidities

Diabetes mellitus (DM) was defined by any of the following: hemoglobin A1c (HbA1c) > 6.4%, fasting blood glucose (FBG) ≥ 126 mg/dL (7.0 mmol/L), or use of at least 1 antidiabetic medication. Pre-DM was defined as HbA1c between 5.7% and 6.4% or FBG between 100 and 125 mg/dL (5.6-6.9 mmol/L). Women taking metformin for polycystic ovary syndrome were classified as nondiabetic only if their HbA1c and FBG values both before metformin initiation and at the time of CS diagnosis remained within the normal range. Hypertension was defined as systolic blood pressure ≥ 130 mmHg, diastolic blood pressure ≥ 80 mmHg, or use of any antihypertensive medication.

Statistical Analysis

Analyses were conducted using IBM SPSS for Windows (version 29.0, IBM Corp.). Data normality was assessed by the Shapiro–Wilk test. Descriptive statistics were used for demographic and clinical characteristics. Normally distributed data were compared by Student’s t-test and nonnormally distributed variables with the Mann–Whitney U-test. Paired T-tests were conducted to study mean changes from baseline to a single follow-up visit. For categorical characteristics and the MID, we calculated the achievement rates and used Pearson’s chi-square for comparisons where applicable. For patients with more than 2 follow-up visits ANOVA (repeated measures) was applied for the trajectory of each measurement over time. To identify predictors of improvement, univariable linear regression models for score change and logistic regression for MID achievement were performed using baseline visit and longest follow-up visit for each patient. Variables with P ≤ .10 or of clinical relevance were then entered into multivariable regression models—again, linear regression for score change and logistic regression for MID achievement—where each predictor was separately evaluated, adjusting for age, sex, and baseline score. Correlation analyses were performed using Pearson or Spearman correlation coefficients for data with normal or abnormal distribution, respectively. Correlation coefficients (r) were interpreted as follows: values between 0.0 and ±0.3: weak, between ±0.3 and ±0.7: moderate, and between ±0.7 and ±1.0: strong relationships. All statistical tests were 2-sided, and results were considered significant with P ≤ .05.

Results

Study Participants

From a cohort of 226 endogenous CS and silent ACTH tumor patients enrolled in our ongoing MSKCC prospective cohort study, we identified patients who had a baseline visit with active hypercortisolism, who had at least 1 follow-up visit while in surgical remission or medical control, and who had completed at least 1 of the evaluated questionnaires correctly. After excluding patients with silent ACTH tumors, those with missing data, and follow-up visits that did not meet remission criteria, we included 67 patients (56 females, 11 males) with a mean baseline age of 42.3 ± 13.1 years. Among these patients, 60 had CD and 7 had adrenal CS.

Further patient demographic information is shown in Tables 1 and 2.

 

Table 1.

Demographics and baseline characteristics

Demographic variable n = 67 patients
Age, years
 Mean (SD) 42.3 (13.1)
 Range 20-75
Sex, n (%)
 Female 56 (83.6)
CS subtype, n (%)
 CD 60 (89.6)
 Adrenal CS 7(10.4)
Race, n (%)
 White 50 (74.6)
 Black/African American 8 (11.9)
 Asian 2 (3.0)
 Other/unknown 7 (10.4)
24-hour UFC
 Mean (SD) 391.5 (1471) µg/24 hours,
1080 (4060) nmol/24 hours
 Median (IQR) 135.0 (82.7-220.0) µg/24 hours, 372 (228-607) nmol/24 hours
 Range (min-max) 29-12 346 µg/24 hours, 80-34 053 nmol/24 hours
LNSC, n (%)
 Normal 3 (4.5)
 Abnormal 59 (88.1)
 NA 5 (7.5)
Plasma ACTH
 Mean (SD) 70.7 (64.1) pg/mL, 15.6 (14.1) pmol/L
 Median (IQR) 56.0 (42.0-83.8) pg/mL, 12.3 (9.2-18.4) pmol/L
 Range (min-max) 11-416 pg/mL (2.4-91.5 pmol/L)
Prior recurrence at baseline, n (%) 16 (23.9)
Prior transsphenoidal surgery, n (%) 16 (23.9)
 1 9 (13.4)
 2 7(10.4)

Abbreviations: CD, Cushing disease; CS, Cushing’s syndrome; IQR, interquartile range; LNSC, late-night salivary cortisol; NA, not available; UFC, urinary free cortisol.

 

Table 2.

Baseline and follow-up data

Baseline Longest follow-up P-value
BMI (kg/m2)
 Mean (SD) 33.2 (7.6) 30.6 (8.5) <.001
 Median (IQR) 31.6 (26.8-37.3) 29.3 (25.3-34.8)
LNSC, n (%) <.001
 Normal 3 (4.5) 30 (44.7)
 Abnormal 59 (88.1) 16 (23.8)
 NA 5 (7.5) 21 (31.3)
DM, n (%) <.001
 DM 28 (41.8) 13 (19.4)
 Pre-DM 15 (22.4) 9 (13.4)
Hypertension, n (%) 55 (82.1) 35 (53.7) <.001
HbA1C (%) <.001
 Total mean (SD) 6.5 (1.8) 5.7 (0.9)
 DM/pre-DM mean (SD) 6.9 (1.8) 6.1 (1.0)
Antidiabetic medications, n (%) 20 (29.9) (22.4)
 1 12 (17.9) (13.4)
 2 1 (1.5) (3.0)
 3 3 (4.5) (1.5)
 Insulin 4 (6.0) 3 (4.5)
Antihypertensive medications, n (%) 34 (50.7) (37.3)
 1 15 (22.4) (19.4)
 2 10 (14.9) (11.9)
 ≥3 9 (13.4) 4 (6.0)
Other medications, n (%)
 Antidepressants 10 (14.9) 13 (19.4)
 Anxiolytics 12 (17.9) 12(17.9)
 Pain medications 16 (23.9) 23 (34.3)
 Sleep medications 16 (23.9) 21 (31.3)
Treatment at most recent follow-up,a n (%)
 Transsphenoidal surgery 44 (65.7)
 Medical therapy 18 (26.9)
 Bilateral adrenalectomy 3 (4.5)
 Radiation therapy 1 (1.5)
 Adrenalectomy (adrenal CS) 7 (10.4)

Abbreviations: BMI, body mass index; CS, Cushing’s syndrome; DM, diabetes mellitus; HbA1c, hemoglobin A1c; IQR, interquartile range; LNSC, late-night salivary cortisol.

a“n” refers to number of separate baseline-to-follow-up cases.

In total, there were 46 visits in G1, 31 in G2, and 24 in G3. At the most recent follow-up of each case, there were 24 visits in G1, 25 in G2, and 24 in G3.

The mean (range) duration from baseline to most recent follow-up was 28.3 (5-138) months in the overall cohort. The mean (range) follow-up duration since the most recent treatment was 6.3 (4-9) months for G1, 12.7 (10-18) months for G2, and 43.7 (23-120) months for G3. At their final follow-up visit, 44 patients (65.7%) achieved remission after transsphenoidal surgery (TSS), 18 (26.9%) were under medical control, 3 (4.5%) underwent bilateral adrenalectomy (BLA), 1 (1.5%) received radiation therapy (RT), and the 7 (10.4%) patients with adrenal CS underwent unilateral adrenalectomy (Table 2).

The following additional treatments were administered between this study’s baseline visit and longest follow-up: among the 44 patients treated with TSS at their latest follow-up, 1 underwent an additional TSS and 1 received medical therapy prior to TSS. Of the 18 medically managed patients at last follow-up, 8 (44.4%) had previously undergone TSS (3 of whom had 2 TSSs), and 2 of these 8 additionally received at least 1 different medication before switching to the 1 recorded at their last follow-up. Two (11.1%) other patients received 2 sequential medications before the final 1 at follow-up, and 1 (5.6%) patient was on a block-and-replace regimen with hydrocortisone (HC) after 2 TSSs and BLA. The complete treatment journey of patients on medical therapy, before and after entering the study, is shown in Fig. 1. Among the patients who underwent BLA at last follow-up, 1 had 2 prior TSSs, 1 had a sin1 gle prior TSS and received medical therapy and had 2 TSSs and received medical therapy. The patient treated with RT had 2 prior TSSs and received medical therapy.

 

Treatment journey of the 18 patients on medical therapy at their longest follow-up. Each row represents the longitudinal treatment course of each patient before and/or after entering the study. Multiple boxes indicating medical therapy within the same patient represent different medications administered over time. Segments outlined in bold represent the follow-up period analyzed in the current cohort, from this' study baseline to the longest available follow-up.

Figure 1.

Treatment journey of the 18 patients on medical therapy at their longest follow-up. Each row represents the longitudinal treatment course of each patient before and/or after entering the study. Multiple boxes indicating medical therapy within the same patient represent different medications administered over time. Segments outlined in bold represent the follow-up period analyzed in the current cohort, from this’ study baseline to the longest available follow-up.

Abbreviations: CT, clinical trial; Keto, ketoconazole; Levo, levoketoconazole; Mety, metyrapone; Mife, mifepristone; Osilo, osilodrostat; Pasi, pasireotide.

Sixteen patients presented with recurrent disease; an additional 9 patients (13.4%) developed recurrent or persistent disease after surgery. HC replacement was administered at 21 of the longest available follow-up visits [6 due to ongoing hypopituitarism or adrenal insufficiency (AI) and 15 for temporary postoperative AI], with another 9 cases receiving replacement at intermediate follow-up visits.

All 18 patients on medical therapy at their longest follow-up received adrenal steroidogenesis inhibitors: osilodrostat (8 patients, 44.4%), metyrapone (6 patients, 33.3%), and ketoconazole (4 patients, 22.2%).

Comorbid Conditions

As shown in Table 2, mean body mass index (BMI) at baseline was 33.2 ± 7.6 kg/m2. Twenty-eight (41.8%) patients presented with DM, 15 (22.4%) with prediabetes, and 24 (35.8%) without DM. Fifty-five of 67 patients (82.1%) had hypertension at baseline. At the longest follow-up, mean BMI decreased to 30.6 ± 8.5 kg/m² (P < .001), and mean HbA1c decreased to 5.7 ± 0.9% (P < .001). Thirteen patients (19.4%) continued to have DM, and 9 patients (13.4%) had prediabetes. Hypertension was present in 35 patients (53.7%), of whom 25 (71.4%) were receiving at least 1 antihypertensive medication.

LNSC levels remained abnormal in 16 patients (23.8%), although LNSC data were not available for 21 patients (31.3%). Of those, LNSC testing was not considered clinically indicated in some cases, such as patients on HC replacement for postoperative AI (n = 10) or patients with adrenal CS status postadrenalectomy (n = 3). The remaining 8 patients with missing LNSC data were on medical therapy (n = 4) or status post-TSS (n = 4).

Cushing QoL

Sixty-five patients (71 baseline to follow-up case pairs) completed the CushingQoL assessment. In the overall cohort, treatment resulted in significant improvements in mean QoL scores at all follow-up time points: mean change in G1 was 16.6 ± 18.6 (P < .001); G2, 19.1 ± 19.4 (P < .001); and G3, 16.6 ± 27.1 (P = .009) (Table 3Fig. 2A). For longest available follow-up for each case, overall mean improvement was 18.2 ± 20.9 points (P < .001).

 

Score trajectory for (A) Cushing QoL, (B) BDI-II, (C) STAI-State, and (D) STAI-Trait in the overall cohort based on duration of follow-up, including patients with 2 follow-up visits. Significant improvements in mean scores were observed in all assessments and all follow-up time points except in group 3 STAI-State, noted with a gray line. Group 1: 6 months posttreatment, group 2: 12 to 18 months posttreatment, group 3: ≥ 24 months posttreatment.

Figure 2.

Score trajectory for (A) Cushing QoL, (B) BDI-II, (C) STAI-State, and (D) STAI-Trait in the overall cohort based on duration of follow-up, including patients with 2 follow-up visits. Significant improvements in mean scores were observed in all assessments and all follow-up time points except in group 3 STAI-State, noted with a gray line. Group 1: 6 months posttreatment, group 2: 12 to 18 months posttreatment, group 3: ≥ 24 months posttreatment.

Abbreviations: BDI-II, Beck Depression Inventory-II; QoL, quality of life; STAI, State-Trait Anxiety Inventory.

 

Table 3.

Cushing QoL scores at baseline, follow-up visit, and mean score change in each time-based group for total cohort, patients who had TSS and patients on medical therapy

Category Subgroup n Baseline mean Follow-up visit mean Mean change SD (change) P-value
Total cohort Longest follow-up 71 42.4 60.6 18.2 20.9 <.001
Group 1 45 40.6 57.2 16.6 18.6 <.001
Group 2 30 43.5 62.6 19.1 19.4 <.001
Group 3 23 41.2 57.9 16.6 27.1 .009
TSS Longest follow-up 42 40.0 59.9 20.0 18.5 <.001
Group 1 29 40.2 57.0 16.8 19.1 <.001
Group 2 21 41.4 61.9 20.4 15.8 <.001
Group 3 9 29.0 48.7 19.7 24.9 .045
Medical therapy Longest follow-up 19 46.3 58.4 12.1 26.2 .059
Group 1 9 44.6 56.7 12.1 18.5 .086
Group 2 7 40.9 57.1 16.3 31.4 .219
Group 3 10 56.0 62.0 6.0 27.9 .513

Abbreviations: QoL, quality of life; TSS, transsphenoidal surgery.

In the subanalysis by treatment strategy, 42 patients who completed the Cushing QoL achieved surgical remission and 19 patients were controlled on medical therapy. In the surgical cohort, improvement in scores were noted across all time groups with a mean score increase of 20.0 ± 18.5 points from baseline to the longest available follow-up (P < .001) (Figs. 3A and 4A). Among these patients, 15 had 2 follow-up visits; between them the mean score further increased by 9.6 ± 14.8 points, indicating significant QoL improvement >6 months postsurgery (P  = .025). In contrast, patients under medical control at follow-up showed a mean improvement of 12.1 ± 26.2 points from baseline to the longest follow-up, which did not reach statistical significance (n = 19; P  = .059) (Table 3Figs. 3A and 4A).

 

Mean score change in total cohort, patients after transsphenoidal surgery, and patients on medical therapy based on duration of follow-up: (A) Cushing QoL, (B) BDI-II, (C) STAI-State, (D) STAI-Trait. Direct comparison between the 2 treatment modalities was performed only in the longest available follow-up visit for each patient. Caps represent SEM. Only P-values ≤ .05 are displayed.

Figure 3.

Mean score change in total cohort, patients after transsphenoidal surgery, and patients on medical therapy based on duration of follow-up: (A) Cushing QoL, (B) BDI-II, (C) STAI-State, (D) STAI-Trait. Direct comparison between the 2 treatment modalities was performed only in the longest available follow-up visit for each patient. Caps represent SEM. Only P-values ≤ .05 are displayed.

Abbreviations: BDI-II, Beck Depression Inventory-II; QoL, quality of life; STAI, State-Trait Anxiety Inventory.

 

Mean scores at baseline and longest follow-up in total cohort, patients after transsphenoidal surgery, and patients on medical therapy for (A) Cushing QoL, (B) BDI-II, (C) STAI-State, (D) STAI-Trait. Caps represent SEM. Asterisks (*) indicate significant change from baseline to follow-up (P ≤ .05) and brackets significant differences between the 2 treatment modalities at the longest follow-up visit (P ≤ .05).

Figure 4.

Mean scores at baseline and longest follow-up in total cohort, patients after transsphenoidal surgery, and patients on medical therapy for (A) Cushing QoL, (B) BDI-II, (C) STAI-State, (D) STAI-Trait. Caps represent SEM. Asterisks (*) indicate significant change from baseline to follow-up (P ≤ .05) and brackets significant differences between the 2 treatment modalities at the longest follow-up visit (P ≤ .05).

Abbreviations: BDI-II, Beck Depression Inventory-II; QoL, quality of life; STAI, State-Trait Anxiety Inventory.

MID achievement and predictors of improvement

In the overall cohort, CushingQoL MID was achieved in 42 of the 65 patients (64.6%) (Fig. 5). When stratified by follow-up duration, MID achievement rates were 60.8% in G1 (n = 45), 70.0% in G2 (n = 30), and 60.9% (n = 23) in G3.

 

MID achievement rates for all patient-reported outcomes at most recent follow-up.

Figure 5.

MID achievement rates for all patient-reported outcomes at most recent follow-up.

Abbreviations: MID, minimal important difference.

Males (n = 11) improved more than female patients (n = 54) (27.8 ± 13.0 vs 15.5 ± 21.9; P  = .020) and achieved the MID more frequently (90.9% vs 59.3%; P  = .045). Even though they presented with lower baseline scores compared to females (33.2 ± 16.3 vs 44.3 ± 20.7), that difference was not significant (P  = .117).

Score change differed by BMI category, using as cut-off the baseline mean of our cohort (≤33.2 vs >33.2 kg/m²): patients with lower BMI (n = 34) improved considerably more than those with higher BMI (n = 31) (median score change: 26 vs 11; P = .023). Likewise, MID achievement was more common in the low-BMI group (76.5% vs 51.6%; P = .036).

Patients presenting with recurrent disease at baseline (n = 16) reported better baseline QoL than those with primary disease (n = 49) (51.6 ± 19.5 vs 39.5 ± 20.9; P = .046), and their mean improvement following treatment was smaller (7.2 ± 21.0 vs 21.0 ± 19.8; P = .022). Only 43.8% of recurrent cases achieved the MID compared to 71.4% of primary cases (P = .044).

Patients reporting symptom duration ≥3 years prior to diagnosis (n = 29) were less likely to achieve the MID compared to those with shorter symptom duration (n = 35) (48.3% vs 66.7%; P = .008).

Patients with at least 1 abnormal LNSC (n = 15) value at follow-up were less likely to meet MID compared to those with normal LNSC values (n = 28) (33.3% vs 75.0%; P = .008). Similarly, patients requiring HC replacement (after their first TSS or unilateral adrenalectomy for adrenal CS) for >6 months (n = 22) were more likely to achieve MID than those requiring ≤6 months (n = 30) (81.8% vs 50.0%; P = .019).

MID achievement rates between the TSS and medical-therapy groups differed (71.4% vs 47.4%) but did not reach significance (P = .070).

Baseline 24 hours UFC was inversely correlated with baseline CushingQoL score (ρ = −0.3; P = .035), indicating a relationship between biochemical and symptomatic disease severity.

BDI-II

Fifty-six patients (60 case pairs) were included in this subgroup. In the overall cohort, improvements in BDI-II score were seen at all follow-up time points: mean change in G1 was 4.7 ± 9.2 (P = .004); in G2, 7.7 ± 7.3 (P  < .001); and in G3, 7.6 ± 10.6 (P = .008). In the overall cohort, mean improvement from baseline to the longest follow-up was 6.8 ± 8.6 points (P  < .001) (Table 4Fig. 2B). Of note, a significant 7.3-point improvement was noted between follow-up G1 (6 months) and follow-up G2 (12 months) (n = 11, P = .025), indicating continued improvement in depressive symptoms over time after treatment.

 

Table 4.

BDI-II scores at baseline, follow-up visit, and mean score change in each time-based group for total cohort, patients who had TSS and patients on medical therapy

Category Subgroup n Baseline mean Follow-up visit mean Mean change SD (change) P-value
Total cohort Longest follow-up 60 15.7 8.9 6.8 8.6 <.001
Group 1 37 17.0 12.2 4.7 9.2 .004
Group 2 26 15.2 7.5 7.7 7.3 <.001
Group 3 18 15.9 8.3 7.6 10.6 .008
TSS Longest follow-up 32 17.1 8.2 8.8 8.1 <.001
Group 1 22 18.6 13.6 5.0 10.9 .043
Group 2 17 14.7 6.7 8.0 8.1 <.001
Group 3 6 20.5 8.3 12.2 4.7 .001
Medical therapy Longest follow-up 18 14.4 11.0 3.4 9.9 .159
Group 1 8 14.6 11.0 3.6 6.7 .171
Group 2 6 18.3 10.8 7.5 7.1 .049
Group 3 9 11.8 8.8 3.0 13.3 .517

Abbreviations: BDI-II, Beck Depression Inventory-II; TSS, transsphenoidal surgery.

Among the 32 patients who underwent TSS, improvements were noted across all follow-up time groups, with mean scores decreasing from 17.1 ± 10.9 to 8.2 ± 7.0 at the longest follow-up (P  < .001). In contrast, the 18 patients treated medically did not experience a significant change (P = .159). Improvement following TSS was significantly greater than with medical therapy at longest follow-up for each case (8.8 ± 8.1 vs 3.4 ± 9.9; P = .043) (Figs. 3B and 4B).

MID achievement and improvement predictors

Thirty-eight patients (67.9%) achieved MID by their longest follow-up (Fig. 5). Twenty-nine (51.8%) patients had baseline scores ≥14 points, indicating mild or moderate depression, and 23 (79.3%) of these patients met the MID. By follow-up duration, overall MID achievement rates were 56.8% in G1 (n = 37), 76.9% in G2 (n = 26), and 72.2% in G3 (n = 18).

By treatment approach, MID was met by 75.0% of patients who had TSS (n = 32) and 38.9% of patients on medication (n = 18) (P = .012). All patients who underwent BLA (n = 4) or RT (n = 1) and 5 out of 6 patients treated for adrenal CS achieved MID.

Patients with recurrent and primary disease did not differ in terms of baseline score (P = .267). However, those with recurrent disease were less likely to achieve MID (42.9% vs 76.2%; n = 14 vs 75.6%; n = 42, P = .021).

Symptom duration prior to diagnosis was inversely correlated with BDI-II score change (ρ = −0.33, P = .016). Patients experiencing symptoms for ≥3 years (n = 24) exhibited lower MID achievement rates compared to those with shorter symptom duration (n = 31) (50.0% vs 83.9%; P = .007).

Patients with normal LNSC at follow-up had higher MID achievement rates (81.5%; n = 27 vs 45.5%; n = 11, P = .026).

STAI

STAI-S

Fifty-six patients (60 case pairs) completed the STAI-State questionnaire. All follow-up time groups exhibited improvements, although in G3 the score decrease did not reach significance. In the overall cohort, mean scores declined from 44.8 ± 14.0 to 35.3 ± 11.2 at the longest follow-up (P < .001) (Table 5).

 

Table 5.

STAI scores at baseline, follow-up visit, and mean score change in total cohort, patients who had TSS and patients on medical therapy

Outcome Category Subgroup n Baseline mean Follow-up visit mean Mean change SD (change) P-value
STAI-State Total cohort Longest follow-up 60 44.8 35.3 9.6 12.5 <.001
Group 1 40 45.9 36.6 9.3 12.3 <.001
Group 2 25 46.2 35.3 10.8 10.8 <.001
Group 3 17 42.4 36.1 6.3 13.8 .078
TSS Longest follow-up 33 44.4 34.3 10.1 12.3 <.001
Group 1 24 44.4 35.8 8.6 11.9 .002
Group 2 16 43.7 33.9 9.8 11.9 .005
Group 3 7 46.0 37.9 8.1 12.1 .126
Medical therapy Longest follow-up 17 47.2 37.4 9.8 14.7 .014
Group 1 9 50.9 37.2 13.7 13.7 .017
Group 2 5 56.4 39.8 16.6 8.4 .012
Group 3 8 36.3 34.6 2.0 14.9 .715
STAI-Trait Total cohort Longest follow-up 58 46.0 37.3 8.6 12.6 <.001
Group 1 36 47.9 40.3 7.6 12.0 <.001
Group 2 26 45.7 36.0 9.6 10.9 <.001
Group 3 16 46.7 36.9 9.8 13.2 .010
TSS Longest follow-up 31 47.5 36.7 10.7 12.2 <.001
Group 1 22 47.9 40.6 7.3 11.5 .008
Group 2 16 46.3 35.9 10.4 11.4 .002
Group 3 6 54.0 37.8 16.2 7.5 .003
Medical therapy Longest follow-up 18 45.1 38.8 6.2 13.4 .065
Group 1 8 49.5 39.8 9.8 14.0 .089
Group 2 6 47.5 36.2 11.3 10.9 .052
Group 3 8 39.3 37.5 1.8 12.7 .709

Abbreviations: STAI, State-Trait Anxiety Inventory; TSS, transsphenoidal surgery.

By treatment modality, state anxiety improved in both the TSS group (10.1 ± 12.3; n = 33; P < .001) and patients on medical therapy (9.8 ± 14.7; n = 17; P = .014) (Figs. 3C and 4C).

MID achievement and improvement predictors

Overall, 30 of 56 (53.5%) patients achieved MID in STAI-State at their longest follow-up visit (Fig. 5). By follow-up duration, MID achievement rates were 52.5% in G1 (n = 40), 56.1% in G2 (n = 25), and 64.7% in G3 (n = 17).

A negative correlation was observed between STAI-S score change and baseline age (ρ = −0.3, P = .029). Patients >40 years old at baseline (n = 29), improved less than younger patients (n = 27) [median score change: 5 vs 13 (P = .017)] and were less likely to meet the MID, with results approaching statistical significance (41.4% vs 66.7%, P = .058).

STAI-T

Fifty-three patients (58 case pairs) were evaluated. In the overall cohort, mean score change from baseline to longest follow-up was 8.6 ± 12.6 points (P < .001). In time-based subgroups the following score reductions were noted: G1: 7.6 ± 12.0 (P < .001), G2: 9.6 ± 10.9 (P < .001), G3: 9.8 ± 13.2 (P = .010) (Fig. 2D). Among patients treated with TSS (n = 31), significant improvement was seen in every subgroup. Patients receiving medical therapy (n = 18) showed numerical but not statistically significant improvement (P = .065) (Table 5Figs. 3D and 4D).

MID achievement and improvement predictors

STAI-Trait MID was achieved by 28 (52.8%) patients at the longest follow-up (Fig. 5). By follow-up duration, MID achievement rates were 44.4% in G1, 53.8% in G2, and 68.8% in G3.

Patients ≤40 years at baseline (n = 26) improved more than those aged >40 years (n = 27), with results approaching significance [median score change: 14 vs 4 (P = .060)].

Patients with ≥2 Follow-up Visits

Twenty-eight patients had multiple follow-up visits; we stratified by follow-up duration (<2 years vs ≥2 years) [Table S1 (30)].

Cushing QoL

Significant improvements were noted in all groups with pairwise comparisons revealing higher scores in both first and second follow-up, with the mean score changing by 14.9 (P = .002) and 21.5 (P < .001) points, respectively, in total cohort.

BDI-II

Although the overall trajectory demonstrated significant improvement, pairwise comparisons showed no significant changes between baseline and first follow-up. Improvement was noted between baseline and the second follow-up visit (P < .001) and between the 2 treated visits (P = .021) (Table 6).

 

Table 6.

BDI-II mean scores and pairwise comparisons in patients with 2 follow-up visits

Comparison Mean score A Mean score B Mean difference P-value
Baseline vs follow-up 1 16.9 13.0 4.846 .200
Baseline vs follow-up 2 16.9 7.1 9.731 <.001
Follow-up 1 vs follow-up 2 13.0 7.1 4.885 .021

Abbreviations: BDI-II, Beck Depression Inventory-II.

STAI-S

Overall, the mean score decreased from 45.9 ± 13.0 at baseline to 38.3 ± 12.4 at the first follow-up and to 36.1 ± 10.9 at the second follow-up (P = .005). In cases with follow-up ≥2 years (n = 13), the score trajectory did not change significantly from baseline (P = .187). In contrast, patients with total follow-up <2 years (n = 11) exhibited significant improvement (P = .008).

STAI-T

Overall, the mean score decreased from 49.2 ± 9.0 at baseline to 39.8 ± 11.6 at first follow-up and further to 36.4 ± 10.5 at second follow-up (P < .001). Significant improvement noted from baseline to both follow-up visits in both subgroups (P < .001).

Regression Analyses for Predictors of Change

In all measurements, after controlling for age and sex, baseline score was an independent predictor of greater change (P < .001) (Table 7). Patients with more impaired QoL, or severe depression and anxiety at baseline, had more room for improvement.

 

Table 7.

Predictors of mean score change from baseline to most recent follow-up of each patient in univariable and multivariable linear regression analysis

Outcome Parameter Univariable analysis Multivariable analysis
Estimate SE P-value Estimate SE P-value
Cushing QoL score change Baseline score −0.50 0.11 <.001 −0.47 0.11 <.001
Baseline age −0.05 0.20 .797 −0.04 0.19 .825
Male sex 12.11 6.83 .081 7.49 6.68 .267
Baseline age ≤40 (vs >40) −3.43 5.23 .515 −4.90 4.89 .321
Normal LNSC (vs abnormal) −19.98 6.4 .004 −19.39 5.26 .001
HC replacement >6 months (vs ≤6 months) 10.06 5.90 .095 12.35 4.96 .016
Primary disease at baseline (vs recurrent) −13.19 5.86 .028 −6.63 5.60 .241
Baseline BMI ≤33.2 kg/m2 (vs >33.2 kg/m2) −8.72 5.1 .095 −6.53 4.71 .171
Symptom duration ❤ years (vs ≥3 years) −4.60 5.25 .384 −4.55 4.70 .337
Treatment (TSS vs medical therapy) −7.87 5.8 .185 −4.23 5.41 .473
BDI-II score change Baseline score 0.57 0.09 <.001 0.58 0.09 <.001
Baseline age −0.08 0.09 .402 0.02 0.08 .797
Male sex −0.59 3.07 .848 0.80 2.53 .752
Baseline age ≤40 (vs >40) −3.96 4.82 .429 −0.52 2.02 .800
Normal LNSC (vs abnormal) −3.01 3.06 .332 −3.27 1.87 .090
HC replacement >6 months (vs ≤6 months) 0.06 2.577 .980 2.33 1.90 .226
Primary disease at baseline (vs recurrent) −4.76 2.63 .076 −2.66 2.17 .224
Baseline BMI ≤33.2 kg/m2 vs >33.2 kg/m2 −3.79 2.29 .104 −1.41 1.90 .462
Symptom duration ❤ years (vs ≥3 years) −5.61 2.23 .015 −3.49 1.78 .055
Treatment (TSS vs medical therapy) −5.46 2.60 .041 −3.94 2.02 .057
STAI-State score change Baseline score 0.57 0.09 <.001 0.56 0.09 <.001
Baseline age −0.22 0.13 .104 −0.11 0.12 .338
Male sex −5.70 4.37 .197 −4.39 3.69 .239
Baseline age ≤40 (vs >40) −5.94 3.30 .078 −3.75 2.73 .175
Normal LNSC (vs abnormal) −2.15 3.95 .589 −4.47 2.89 .131
HC replacement >6 months (vs ≤6 months) 0.72 3.45 .836 4.42 2.81 .123
Primary disease at baseline (vs recurrent) 2.41 3.91 .743 2.14 2.91 .465
Baseline BMI ≤33.2 kg/m2 (vs >33.2 kg/m2) −2.36 3.38 .488 −0.93 2.56 .716
Symptom duration ❤ years (vs ≥3 years) −5.67 3.33 .095 −3.26 2.46 .192
Treatment (TSS vs medical therapy) −1.50 3.91 .970 −2.77 2.97 .355
STAI-Trait score change Baseline score 0.58 0.11 <.001 0.56 0.12 <.001
Baseline age −0.20 0.13 .128 −0.07 0.11 .562
Male sex −3.09 4.57 .502 −0.83 4.13 .841
Baseline age ≤40 (vs >40) −5.45 3.36 .111 −2.55 3.03 .405
Normal LNSC (vs abnormal) −6.52 4.23 .133 −6.74 3.44 .059
HC replacement >6 months (vs ≤6 months) 4.63 3.52 .195 7.11 2.87 .018
Primary disease at baseline (vs recurrent) −2.07 3.90 .597 −0.34 3.42 .921
Baseline BMI ≤33.2 kg/m2 (vs >33.2 kg/m2) −4.95 3.38 .150 −2.59 3.00 .393
Symptom duration ❤ years (vs ≥3 years) −5.78 3.37 .093 −4.35 2.80 .127
Treatment (TSS vs medical therapy) −4.49 3.74 .236 −3.39 3.11 .281

Each predictor in multivariable analysis was separately evaluated, adjusting for baseline age, sex, and baseline score. In models exploring baseline age <40 years as a categorical variable, continuous baseline age was not included in the multivariable model. Statistically significant results (P ≤ .05) are indicated in bold.

Abbreviations: BDI-II, Beck Depression Inventory-II; BMI, body mass index; HC, hydrocortisone; LNSC, late-night salivary cortisol; QoL, quality of life; STAI, State-Trait Anxiety Inventory; TSS, transsphenoidal surgery.

Cushing QoL

Normal LNSC at follow-up and >6 months of postoperative HC replacement were predictors of QoL score improvement and MID achievement even after adjustment for baseline score, age, and sex. Lower baseline BMI and male sex, although significant in univariable analysis, were no longer significant in the multivariable linear model. However, a BMI < 33.2 kg/m² (P = .034) and symptom duration ❤ years prior to diagnosis (P = .005) remained statistically significant predictors of reaching the MID in the multivariable logistic model (Table 8Fig. 6). To determine if treatment modality modified the effect of LNSC, we built a model including baseline QoL score, age, sex, follow-up LNSC, and treatment type (TSS vs medical therapy). In this multivariable model, normal LNSC remained a significant predictor of improvement (P = .023).

 

MID achievement predictors after multivariable analysis for (A) Cushing QoL, (B) BDI-II, (C) STAI-State. Each predictor was analyzed in a separate logistic regression model after adjustment for baseline score, age, and sex. Predictors for trait anxiety are not shown, as a longer duration of postoperative HC replacement was a significant predictor only in the linear multivariable regression model.

Figure 6.

MID achievement predictors after multivariable analysis for (A) Cushing QoL, (B) BDI-II, (C) STAI-State. Each predictor was analyzed in a separate logistic regression model after adjustment for baseline score, age, and sex. Predictors for trait anxiety are not shown, as a longer duration of postoperative HC replacement was a significant predictor only in the linear multivariable regression model.

Abbreviations: BDI-II, Beck Depression Inventory-II; HC, hydrocortisone; LNSC, late-night salivary cortisol; QoL, quality of life; STAI, State-Trait Anxiety Inventory; TSS, transsphenoidal surgery.

 

Table 8.

Predictors of MID achievement from baseline to most recent follow-up of each patient in univariable and multivariable logistic regression models

Outcome Parameter Univariable analysis Multivariable analysis
Estimate SE P-value Estimate SE P-value
Cushing QoL MID achievement Baseline score 0.94 0.02 <.001 0.94 0.02 <.001
Baseline age 1.01 0.02 .548 1.02 0.03 .410
Male sex 6.89 1.09 .076 3.82 1.16 .249
Baseline age ≤40 (vs >40) 1.01 0.52 .987 1.27 0.62 .704
Normal LNSC (vs abnormal) 6.00 0.70 .011 22.82 1.17 .007
HC replacement >6 months (vs ≤6 months) 4.50 0.66 .023 14.49 0.99 .007
Primary disease at baseline (vs recurrent) 3.21 0.60 .050 1.78 0.68 .400
Baseline BMI ≤33.2 kg/m2 (vs >33.2 kg/m2) 3.05 0.54 .039 4.33 0.69 .034
Symptom duration ❤ years (vs ≥3 years) 4.29 0.56 .010 9.07 0.78 .005
Treatment (TSS vs medical therapy) 2.79 0.57 .074 2.36 0.68 .209
BDI-II MID achievement Baseline score 1.08 0.04 .064 1.08 0.04 .042
Baseline age 1.02 0.02 .510 1.01 0.03 .613
Male sex 5.28 1.10 .130 5.76 1.14 .126
Baseline age ≤40 (vs >40) 1.11 0.57 .854 1.05 0.63 .937
Normal LNSC (vs abnormal) 5.28 0.78 .033 14.86 1.25 .030
HC replacement >6 months (vs ≤6 months) 2.00 0.65 .288 2.32 0.71 .236
Primary disease at baseline (vs recurrent) 4.27 0.65 .026 2.67 0.71 .165
Baseline BMI ≤33.2 kg/m2 (vs >33.2 kg/m2) 1.94 0.58 .255 1.55 0.66 .504
Symptom duration < 3 years (vs ≥3 years) 5.20 0.64 .010 5.74 0.70 .012
Treatment (TSS vs medical therapy) 4.71 0.63 .014 4.19 0.69 .039
STAI-State MID achievement Baseline score 1.17 0.04 <.001 1.19 0.05 <.001
Baseline age 0.97 0.02 .241 0.96 0.03 .261
Male sex 1.95 0.71 .347 3.17 1.00 .249
Baseline age ≤40 (vs >40) 2.83 0.56 .061 5.87 0.89 .048
Normal LNSC (vs abnormal) 2.02 0.73 .337 2.41 1.04 .396
HC replacement >6 months (vs ≤6 months) 0.94 0.59 .943 2.66 0.97 .313
Primary disease at baseline (vs recurrent) 1.21 0.62 .757 2.15 0.92 .408
Baseline BMI ≤33.2 kg/m2 (vs >33.2 kg/m2) 2.05 0.54 .189 1.57 0.82 .584
Symptom duration < 3 years (vs ≥3 years) 1.39 0.55 .52 0.98 0.77 .980
Treatment (TSS vs medical therapy) 1.95 0.62 .279 1.44 0.78 .634
STAI-Trait MID achievement Baseline score 1.17 0.05 <.001 1.17 0.05 <.001
Baseline age 0.98 0.02 .295 0.97 0.03 .342
Male sex 2.33 0.75 .257 4.16 1.02 .161
Baseline age ≤40 (vs >40) 2.12 0.56 .175 2.32 0.76 .265
Normal LNSC (vs abnormal) 1.78 0.71 .416 1.48 0.96 .686
HC replacement >6 months (vs ≤6 months) 1.58 0.60 .450 4.21 0.95 .130
Primary disease at baseline (vs recurrent) 2.45 0.61 .138 2.06 0.90 .421
Baseline BMI ≤33.2 kg/m2 (vs >33.2 kg/m2) 1.98 0.54 .202 1.11 0.79 .891
Symptom duration < 3 years (vs ≥3 years) 1.09 0.53 .866 0.99 0.71 .984
Treatment (TSS vs medical therapy) 1.39 0.60 .585 1.18 0.82 .839

Each predictor in multivariable analysis was separately evaluated, adjusting for baseline age, sex and baseline score. In models exploring baseline age <40 years as a categorical variable, continuous baseline age was not included in the multivariable model. Statistically significant results (P ≤ .05) are indicated in bold.

Abbreviations: BDI-II, Beck Depression Inventory-II; BMI, body mass index; HC, hydrocortisone; LNSC, late-night salivary cortisol; MID, minimal important difference; QoL, quality of life; STAI, State-Trait Anxiety Inventory; TSS, transsphenoidal surgery.

BDI-II

Symptom duration ❤ years (P = .012), normal LNSC at follow-up (P = .030), and TSS (P = .039) instead of medical therapy (for CD) were statistically significant predictors of MID achievement in the multivariable logistic models even after adjusting for age, sex, and baseline score (Table 8Fig. 6).

STAI-S

In the multivariable logistic model adjusted for sex and baseline score, age <40 predicted higher odds of MID achievement (P = .041) (Table 8Fig. 6).

STAI-T

After adjustments for sex and baseline score, age group <40 was no longer a predictor of improvement. Although nonsignificant in univariable screening, duration of postoperative HC replacement >6 months emerged as a significant predictor of score change, though not MID achievement, after adjusting for age, sex, and baseline score (Tables 7 and 8).

Discussion

In a clinical practice cohort of patients with CS followed prospectively before and over time up to 11.5 years after surgical remission and/or biochemical control from medical treatment, we identified significant improvements in mean QoL, depression, and anxiety scores in the overall cohort, but only half of patients achieved clinically meaningful improvements in anxiety, as assessed by MID, and about two-thirds of the cohort achieved clinically meaningful improvements in QoL and depression at their most recent follow-up. When assessed by treatment strategy, surgery resulted in statistically significant improvements in all 3 measures, whereas medical therapy resulted in statistically significant improvements in state anxiety but not QoL or depression. These findings may be impacted by the smaller cohort size of the medically treated patients and more complex treatment journeys in the medically vs surgically treated patients. Overall, in this cohort of treated, biochemically controlled patients, several predictors of improvements were identified, including age, baseline BMI, duration of symptoms prior to treatment, duration of HC requirement after surgery, and LNSC normalization with treatment.

PRO studies in CS have shown that patients with CS are at risk for mood disorders and impaired QoL at diagnosis and that improvement posttreatment is often partial, delayed, or inconsistent, even after biochemical remission (3-12). The most recent prospective study confirmed persistent deficits in QoL and depressive symptoms up to 1 year postsurgery, with mean BDI-II scores remaining in the clinically significant range (9). As for anxiety, a prospective study reported high baseline anxiety in patients with CD, and, although it improved after surgery, a proportion continued to experience anxiety up to 1 year posttreatment (14). Neuroimaging supports a biological basis for these symptoms, with brain abnormalities (hippocampal atrophy, cortical thinning, white matter damage) seen after biochemical cure possibly explaining the long-term emotional and cognitive deficits in some patients (1215). As for previously reported predictors of improvement, male sex, lower BMI at follow-up (43132), LNSC normalization (17), and shorter duration of cortisol exposure (3233) emerged as independent predictors of better QoL. Persistent hormone deficits or arginine vasopressin deficiency were related to worse depression (9) while increased age and male sex predicted less anxiety (31). While some studies suggest that hypopituitarism and HC replacement are associated with poorer outcomes (1134), others found no significant difference (35). Limitations of these studies include the cross-sectional design (431-36), small cohort sizes (9), and lack of long-term follow-up >12 months (37), especially in the setting of clinical trials (17).

In our study, QoL, depression, and anxiety improved following treatment, but the patterns varied by domain and follow-up duration.

As for QoL, interestingly, patients with recurrent disease showed better baseline QoL scores than those with primary disease, possibly due to posttreatment surveillance, resulting in earlier diagnosis at recurrence vs initial presentation. Although patients on medical therapy showed a trend toward improvement with treatment, results did not reach significance, potentially due to sample size or the increased (better) baseline scores in patients with recurrent disease and thus those receiving medical treatment. Most patients on medical therapy had persistent or recurrent disease and have experienced longer, more complex treatment journeys (as depicted in Fig. 1) compared to those in surgical remission, which also may impact QoL and mood outcomes. Notably, in patients with 2 follow-up visits, QoL continued to significantly improve 6 months posttreatment in those treated surgically but not in the total cohort.

Multivariable analysis revealed several predictors of QoL improvement after treatment. LNSC normalization was independently associated with approximately 20 times higher odds of achieving the MID, indicating the clinical importance of recovery of cortisol circadian rhythm for treated CS patients and the need for further work to identify medical therapies and regimens that can facilitate this. Postoperative HC replacement for more than 6 months after surgery (indicating a longer hypothalamic-pituitary-adrenal axis recovery) was also associated with greater QoL improvement. This finding complements prior work showing an association between duration of postoperative HC replacement and long-term remission (3839). Lower baseline BMI and shorter symptom duration were predictive of MID achievement, though not of mean score change.

As for depression, patients with 2 follow-ups had a distinct pattern: no significant change between baseline and first follow-up but significant improvement between the 2 follow-up visits. This suggests that depression may take longer to improve, with more evident change >6 months after biochemical control, which contrasts prior work suggesting that anxiety takes longer than depression to improve (14). The delayed trajectory could reflect the structural brain changes seen in CS even in remission, which are partially reversible (1240). Our data showed that symptom duration > 3 years prior to diagnosis reduced MID achievement, consistent with the literature linking diagnostic delay to persistent depression (33). A normal follow-up LNSC was associated with approximately 15 times higher odds of achieving the MID after adjustment, again emphasizing the need to attempt LNSC normalization while on medical therapy (917).

As for anxiety, to date, no prospective study has assessed anxiety longitudinally using STAI, the gold standard for measuring and differentiating between trait and state anxiety (29). Our results confirm that anxiety improves after treatment; however, state and trait show different patterns. State anxiety was the only domain overall to improve significantly in the medical therapy group, while trait anxiety showed only a trend. Although age <40 predicted greater anxiety improvements in both, this remained significant only for state anxiety after adjustment in the logistic model. Trait anxiety improvements were predicted by longer postoperative HC replacement in the linear multivariable model, again suggesting that a shorter recovery time of the HPA axis may be an early indicator for identifying patients who require a closer follow-up. A normal LNSC at follow-up approached significance in the multivariable linear model, suggesting the importance of circadian rhythm recovery in trait anxiety improvement as well.

Across all measures, we found no baseline or outcome differences between pituitary and adrenal CS or between those on or off HC replacement at their last follow-up. Of note, our cohort was predominantly CD patients, and the small number of adrenal CS patients may limit the ability to detect a difference in the 2 cohorts.

Overall, discrepancies between mean change and MID achievement, as reflected in the linear and logistic models, respectively, highlight the importance of reporting both metrics when available, as they may capture different but clinically useful predictors.

We also observed differences between score change and MID achievement across different time groups within the same questionnaire. In STAI-State, G2 (12-18 months since most recent treatment) had greater score reductions than G3 (24 months or more posttreatment)—though change in G3 was nearly significant. However, a higher proportion of patients in G3 achieved MID. Looking at our data, G3 had the highest SD of mean change, indicating greater heterogeneity in treatment response, likely due to broader range of follow-up duration or higher medical therapy rates among patients: 45.5% (n = 10) in G3 vs 22.6% (n = 6) in G2% and 20% (n = 8) in G1. This variability in state anxiety is reflected in the subgroup of patients with 2 follow-up visits: those followed for >2 years showed no significant improvement, while those with <2 years did. Differential responses to long-term medical therapy, higher rates of loss to follow-up among postsurgical patients, or the negative impact of time on state anxiety symptoms may explain this. For BDI-II we used a percentage-based MID, which likely contributed to greater alignment with mean changes, and accounted for individual variability and baseline severity, factors especially relevant when applying generic tools in disease-specific contexts.

Of note, in the cohort overall, the mean follow-up score was within the normal range for depression (<14 for BDI-II) and anxiety (<40 for STAI) (41). This is an encouraging finding that, on average, patients with treated CS may have rates of depression and anxiety that are not clinically significant. Nevertheless, as shown in Table 2, rates of antidepressant, anxiolytic, pain, and sleep medication use did not decrease with treatment but instead were stable or increased numerically, although they were not statistically significant. Similarly, case-control studies have reported higher depression and anxiety levels in patients with CS in remission when compared to healthy controls, even if the mean scores were within the normal range for both groups (1542). Whether this difference is clinically significant still remains inconclusive. Taken together, these results emphasize the importance of multidisciplinary pituitary centers that integrate formal psychological services, including psychiatric care and social work support, to monitor and promote long-term mental health in this population.

Inclusion of both surgically and medically treated patients may be considered a limitation to the study, since it introduces heterogeneity in the cohort. However, including patients undergoing a range of treatments allows for analysis of CS cohorts as seen in a real-world practice rather than a controlled clinical trial setting, thus providing clinically valuable information. Another limitation of the study is the use of clinically available, rather than centralized, hormone assays, again introducing variability in our data. As this cohort included patients treated at our center, their endocrine testing followed standard of care, which did not include sending samples to a centralized laboratory. The use of antidepressants in a minority of patients could potentially affect depression scores. However, this is an unavoidable reality in patients with CS, and their use was stable over time (14.9% at baseline vs 19.4% at follow-up, P = .49). Given our prospective study design, which captured each patient’s change relative to their own baseline, and adjustment for baseline scores in multivariable models, any confounding is likely limited.

Despite these limitations, our data contribute to the literature as the largest clinical practice cohort to date that prospectively characterizes QoL and mood disturbances in CS patients, before and over time after achieving biochemical control. By incorporating 3 longitudinal time points, we identified that the greatest improvements occur within the first 6 months for QoL and anxiety, while depression improves more gradually beyond that point. Another strength of our approach is the use of score change and MID as outcomes when exploring potential predictors of improvement and not remission score per se, enabling more precise tracking of each patient’s progress and supporting an individualized approach by accounting for baseline severity.

In summary, this prospective analysis of mood and Qol in a clinical practice cohort of patients with CS showed that effective treatment of hypercortisolism improves depression, anxiety, and QoL, but one-third to one-half of patients do not experience clinically meaningful improvements in these measures. We identified predictors of improvement that highlight the need for early detection of CS and treatment strategies that allow for recovery of cortisol circadian rhythm. Psychological recovery in CS is heterogeneous, domain-specific, and not always aligned with biochemical normalization. Our findings support a model of care that extends beyond endocrine remission, integrating psychosocial follow-up and individualized treatment.

Acknowledgments

We would like to thank the people with Cushing’s syndrome who contributed their valuable time to this research.

Funding

This research was funded by the National Institutes of Health/National Cancer Institute Support Grant P30 CA008748.

https://academic.oup.com/jcem/advance-article/doi/10.1210/clinem/dgaf598/8307075?login=false

Prospective Assessment of Mood and Quality of Life in Cushing Syndrome before and after Biochemical Control

Abstract

Context

Cushing syndrome (CS) impairs quality of life (QoL) and mood. Prospective real-life data on post-treatment recovery and predictors of improvement are limited.

Objectives

Evaluate changes in QoL, depression, and anxiety in patients with CS, before and after biochemical control, and identify predictors of clinically meaningful improvement.

Design and Setting

Prospective observational study at a tertiary center.

Patients

67 patients with endogenous CS (60 pituitary, 7 adrenal) were assessed with active disease and again after achieving biochemical control through surgery and/or medication.

Outcomes

Patient-reported outcomes included CushingQoL, Beck Depression Inventory-II (BDI-II), and State-Trait Anxiety Inventory (STAI).

Results

Mean and longest follow-up was 2.3 and 11.5 years, respectively. Treatment led to improvements in mean scores across all domains (QoL: +18.2±20.9, BDI: –6.8±8.6, STAI-State: –9.6±12.5, STAI-Trait: –8.6±12.6; all p < 0.001). However, minimal important difference was achieved in 64.6% for QoL, 67.9% for BDI, 53.2% and 52.8% for STAI subscales. After multivariable analysis, QoL improvements were predicted by lower baseline BMI, pre-treatment symptoms ❤ years, post-operative hydrocortisone replacement >6 months, and normal follow-up late-night salivary cortisol (LNSC). Depression improvements were predicted by symptoms ❤ years, normal follow-up LNSC, and surgical treatment. Anxiety improvements were predicted by younger age and >6 months post-operative hydrocortisone. Depression improved more gradually than QoL and anxiety.

Conclusions

Although effective treatment improves mood and QoL in CS, clinically meaningful recovery is variable and incomplete for some patients. Our findings highlight the need to limit diagnostic delay and provide comprehensive post-treatment care that includes normalization of cortisol circadian rhythm.

Accepted manuscripts
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Crinetics Pharma’s Promising Study on CRN04894 for Cushing’s Syndrome: A Potential Game-Changer?

Crinetics Pharmaceuticals is conducting a study titled ‘A Phase 1b/2a Open-label Multiple-ascending Dose Exploratory Study of CRN04894 in ACTH-dependent Cushing’s Syndrome.’ This study aims to evaluate the safety, tolerability, and pharmacokinetics of CRN04894, an ACTH receptor antagonist, in treating Cushing’s Syndrome, a condition characterized by excessive cortisol production. The study’s significance lies in its potential to offer a new treatment avenue for patients with Cushing’s disease or Ectopic ACTH Syndrome.

The intervention being tested is a drug named atumelnant, which is an orally active agent designed to block the action of ACTH at its receptor. This intervention is administered in tablet form and is intended to manage the symptoms of ACTH-dependent Cushing’s Syndrome.

The study employs an interventional design with a sequential model, featuring multiple ascending doses over 10 to 14 days. It is open-label, meaning there is no masking, and its primary purpose is treatment-focused, aiming to assess the drug’s effects on participants.

The study began on March 27, 2023, and is currently recruiting participants. The last update was submitted on April 8, 2025. These dates are crucial as they indicate the study’s progress and ongoing nature, which is essential for stakeholders tracking its development.

This clinical update could influence Crinetics Pharma’s stock performance positively by showcasing their commitment to advancing treatment options for Cushing’s Syndrome. Investors may view this as a promising development, potentially enhancing market sentiment. The study’s progress should be monitored alongside competitors in the endocrinology space to gauge its broader industry impact.

https://www.tipranks.com/news/company-announcements/crinetics-pharmas-promising-study-on-crn04894-for-cushings-syndrome-a-potential-game-changer

The Impact of Adrenalectomy On Metabolic Outcomes of Patients Wwth Mild Autonomous Cortisol Secretion Defined by Low-Dose Dexamethasone Suppression Testing

Abstract

Background

Up to 50% of patients with adrenal incidentalomas have mild autonomous cortisol secretion, which may increase their cardiometabolic morbidity, compared with patients with nonfunctional adrenal tumors. Studies evaluating cardiometabolic outcomes of patients with mild autonomous cortisol secretion defined by 1-mg dexamethasone suppression testing (cortisol 1.8–5 μg/dL) have demonstrated mixed results. The aim of this study was to assess the metabolic outcomes of patients with mild autonomous cortisol secretion, defined by the 1-mg dexamethasone suppression testing criterion, compared with patients with nonfunctional adrenal tumors who underwent adrenalectomy.

Methods

We conducted a single-institution retrospective cohort study comparing adult patients who underwent unilateral adrenalectomy from November 30, 2011, to August 19, 2023, for mild autonomous cortisol secretion (1-mg dexamethasone suppression testing cortisol 1.8–5 μg/dL) or nonfunctional adrenal tumors (1-mg dexamethasone suppression testing cortisol <1.8 μg/dL). Preoperative prevalences and postoperative changes in diabetes mellitus, hypertension, dyslipidemia, and elevated body mass index (≥25) were assessed. Patients were followed from the time of surgery until their last outpatient visit. Multivariable logistic regression was pursued for outcomes that varied between cohorts.

Results

A total of 65 patients (53 mild autonomous cortisol secretion and 12 nonfunctional adrenal tumors) were analyzed. Patients with mild autonomous cortisol secretion were older and more likely to have diabetes mellitus than patients with nonfunctional adrenal tumors (odds ratio: 7.81, 95% confidence interval [0.94, 64.96], P = .04). Patients were followed for a median of 28.1 months [11.1, 55.3 months]. Patients with mild autonomous cortisol secretion were more likely to have postoperative weight improvement (odds ratio: 8.31, [0.97, 71.14], P = .03). After adjusting for clinically relevant variables, the 1-mg dexamethasone suppression testing cortisol was predictive of postoperative weight improvement (odds ratio: 1.88, [1.1, 3.65], P = .04).

Conclusion

Weight loss should be considered as a potential benefit of adrenalectomy in patients with mild autonomous cortisol secretion.

Introduction

Mild autonomous cortisol secretion (MACS) is the most common hormonal abnormality diagnosed in patients with adrenal incidentalomas, impacting 20%–50% of patients.1 Patients with MACS have biochemical evidence of adrenocorticotropic hormone (ACTH)-independent hypercortisolism but lack clinical stigmata commonly associated with overt hypercortisolism, such as facial plethora, abdominal adiposity, extremity weakness and wasting, and/or violaceous striae.2 Overt hypercortisolism is well recognized to cause cardiovascular, musculoskeletal, and metabolic disorders, which have variable resolution even after diagnosis and treatment.3 There is a growing body of evidence that patients with MACS also have increased cardiometabolic morbidity and mortality compared with patients with nonfunctional adrenal tumors,4 but this evidence is challenging to interpret given wide variability in diagnostic criteria that have historically been used.5, 6, 7
Recent guidelines have suggested that a diagnosis of MACS be applied to all patients with a morning (AM) serum cortisol of >1.8 μg/dL after low-dose (1-mg) dexamethasone suppression testing (DST) who lack overt features of hypercortisolism.8,9 However, prior studies comparing cardiometabolic outcomes between patients with MACS and nonfunctional adrenal tumors as well as between patients who underwent operative and nonoperative management have used a 1-mg DST AM serum cortisol of 1.8–5.0 μg/dL as a definition of mild (“subclinical”) hypercortisolism.10, 11, 12, 13, 14, 15, 16 Given that these studies have demonstrated mixed results,4 the primary aim of this study was to assess the metabolic outcomes of patients with MACS, as defined by a 1-mg DST AM cortisol of 1.8–5.0 μg/dL, compared with patients with nonfunctional adrenal tumors who underwent adrenalectomy.

Section snippets

Methods

This was a single-institution retrospective cohort study of patients aged ≥18 years who underwent initial unilateral adrenalectomy from November 30, 2011, to August 19, 2023. Patients were identified through a prospectively maintained database of all patients who underwent adrenalectomy at the study institution. Patients were excluded if they had a 1-mg DST AM serum cortisol of >5 μg/dL, ACTH-dependent hypercortisolism, primary aldosteronism, pheochromocytoma, primary bilateral macronodular

Results

Of the 460 patients who underwent adrenalectomy during the study period, 53 patients met criteria for MACS and 12 patients for nonfunctional adrenal tumors, yielding a cohort of 65 patients. Patients with MACS were older than those with nonfunctional adrenal tumors (MACS, median 60 years [IQR: 54, 68 years] vs nonfunctional adrenal tumors, 49 years [37, 57 years], P = .02) but were similar by sex, race, ethnicity, BMI, nodule size, laterality, and surgical approach (Table II). Among patients

Discussion

MACS is the most common hormonal abnormality diagnosed in patients with adrenal incidentalomas. Despite lacking clinical stigmata of overt hypercortisolism, patients with MACS appear to have increased cardiometabolic morbidity and mortality similar to patients with overt hypercortisolism. The optimal management of MACS is debated, and prior studies using a 1-mg DST AM serum cortisol of 1.8–5.0 μg/dL as a definition of mild hypercortisolism have demonstrated mixed results. Hence, this study

Funding/Support

This project is funded in part by the Advancing a Healthier Wisconsin Endowment at the Medical College of Wisconsin. This publication was supported by the National Center for Research Resources and the National Center for Advancing Translational SciencesNational Institutes of Health (NIH), through grant number UL1TR001436. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the NIH. The grant supports the creation and maintenance of

CRediT authorship contribution statement

Alexa Lisevick Kumar: Writing – original draft, Visualization, Methodology, Formal analysis, Data curation, Conceptualization. Sophie Dream: Writing – review & editing, Validation, Supervision, Methodology, Investigation. Tahseen Shaik: Resources, Project administration, Investigation, Data curation. Kara Doffek: Resources, Project administration, Investigation, Data curation. Ryan Conrardy: Writing – review & editing, Methodology, Formal analysis. James W. Findling: Writing – review & editing,

Conflict of Interest/Disclosure

Dr Findling reports consulting for Corcept, Diurnal, Crinetics and serving as an investigator for Recordati. The rest of the authors reported no biomedical financial interests or potential conflicts of interest.

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A Preliminary Model to Tailor Osilodrostat In Patients With Adrenocorticotropic Hormone (ACTH)-Dependent Cushing’s syndrome

Abstract

Over the past 10 years, osilodrostat has become one of the most commonly used steroidogenesis inhibitors in patients with Cushing’s syndrome. The starting dose is usually determined based on the product characteristics, the prescriber’s experience, and cortisol levels. However, no study has attempted to determine whether there was a dose–response relationship between osilodrostat and cortisol reduction. In this study, we developed a preliminary kinetic–pharmacodynamic model to tailor osilodrostat in patients with Adrenocorticotropin hormone (ACTH)-dependent Cushing’s syndrome. We first analyzed the decrease in cortisol 48 hours after initiation or dose change of osilodrostat in 18 patients. Simulations were then performed for different doses of osilodrostat to evaluate the variation in cortisol concentrations. Our results report the first dose–response relationship between osilodrostat dose and cortisol levels, which should be helpful in identifying the optimal dosing regimen in patients with Cushing’s syndrome and in individualizing treatment to approximate a nychthemeral rhythm.

Significance

The current preliminary study is a first step in trying to better understand the effect of osilodrostat on cortisol, which should help determine the optimal dose for each patient.

Introduction

Cushing’s syndrome is a rare condition in which increased cortisol levels lead to a wide range of comorbidities and increased mortality. Surgery is usually regarded as the first-line and most effective treatment.1 In some cases, cortisol-lowering drugs are necessary, mainly after failed surgery.2,3 Among several steroidogenesis inhibitors such as ketoconazole and metyrapone,4,5 osilodrostat, which acts through inhibition of 11β-hydroxylase, is now being considered an effective drug in controlling cortisol hypersecretion. Initially designed as a CYP11B2 inhibitor, the study by Ménard et al.6 involving both animal models and healthy human subjects showed that osilodrostat reduced cortisol levels from a dose of 1 mg/day, while lower doses exerted an anti-aldosterone effect. Since then, several clinical trials and retrospective studies emphasized its efficacy in all etiologies of Cushing’s syndrome.7-9 While the usual recommended starting dose is 2 mg twice a day, precise studies on the short-term effect of osilodrostat on plasma cortisol are lacking. These data could, however, be of interest to tailor the treatment. Moreover, baseline urinary free cortisol (UFC) level is not able to predict response to osilodrostat.10 Taking advantage of serial cortisol measurements performed in inpatient clinics in our center at the time osilodrostat became available, we developed a pharmacokinetic (PK)/pharmacodynamic model of plasma cortisol variation as a function of osilodrostat dose in patients with Adrenocorticotropin-hormone (ACTH)-dependent Cushing’s syndrome.

Patients and methods

Clinical data and hormonal measurements

We retrospectively included patients with ACTH-dependent Cushing’s syndrome, who had serial measurements of plasma cortisol (every 4 hours for 24 hours) before and after the first osilodrostat dose between 2019 and 2024. These measurements were part of our standard of care approach when osilodrostat became available in our tertiary expert center as a thorough evaluation of the efficacy and tolerance of a new drug. The initial dose ranged from 2 to 15 mg/day, depending on the severity of hypercortisolism. Subsequently, osilodrostat dose was gradually adjusted based on the successive cortisol measurements described above. Sex, age at diagnosis, and etiologies were recorded, as well as plasma cortisol measurements 48 hours after the initiation or any change in the osilodrostat dose and time elapsed since change of dose and last administration were recorded. All plasma cortisol measurements were performed with the same Elecsys II Cortisol, Cobas (Roche Diagnostics) assay in the hormonal laboratory of our center; cross-reactivity with 11-deoxycortisol is 4.9%. According to our institutional policy, this retrospective study did not require specific signed informed consent from patients as the data collected were anonymized. It was thus approved by the Ethics Committee of Assistance Publique—Hopitaux de Marseille (RGPD PADS reference RUXXX2). The current study complies with the Declaration of Helsinki.

Pharmacokinetics and statistical analysis

The pharmacodynamic parameters of osilodrostat on cortisol concentrations were analyzed using a kinetic–pharmacodynamic (PD) model in the software Nonlinear Mixed Effects Modeling version 7.4 (NONMEM Icon Development Solutions, Ellicott City, MD, United States). PK analysis from a previously published study6 was used to predict plasma concentration in our patients. The PK parameters were described in the article, and mean concentration values were obtained by digitizing the graph of osilodrostat vs time using the software WebPlotDigitizer version 4.2.11 With these data, a one-compartment population PK model was used to predict osilodrostat concentrations for different dosing regimens. Direct and indirect relationship between osilodrostat-predicted concentration and variation of cortisol concentrations were evaluated to consider a delay. The variation of cortisol concentrations was calculated with reference to a session without treatment. Several functions were tested to describe the relationship such as linear and sigmoidal. Model selection and evaluation were done by the likelihood ratio test (objective function), goodness-of-fit plots (observed vs predicted variation of cortisol concentrations, observed vs individual predictions, normalized prediction distribution errors vs time and variation of cortisol predictions), bootstrap, and visual predictive checks. Graphical analysis was performed with the R software version 4.4.012 using the ggplot2 package.13 Simulations were performed for different doses of osilodrostat to evaluate the variation on cortisol concentrations using the package rxode2.14

Results

Of the patients who were prescribed osilodrostat at least once between 2019 and 2024, 18 were presenting ACTH-dependent Cushing’s syndrome, 12 women (66.6%) and 6 men (33.3%). Mean age was 53.2 ± 15 years. The cause of Cushing’s syndrome was Cushing’s disease in 16 patients (88.9%), ectopic ACTH secretion in 1 patient (5.6%), and ACTH-dependent hypercortisolism of uncertain diagnosis in 1 patient (5.6%). Clinical characteristics are presented in Table 1. It should be noted that none of the patients included were Asian.

 

 

Table 1.

Clinical characteristics of patients with all included patients and differentiated according to gender.

All patientsa Women Men
Age at diagnosis 53.2 ± 15 54 ± 17.2 51.5 ± 10.5
Weight 81.7 ± 13.7 79.5 ± 12.7 86.2 ± 15.6
% of CD 88.9 83.3 100
ULN of 24 hour UFC 4.4 ± 8.3 5.5 ± 10.3 2.5 ± 1.8
Osilodrostat starting dose 3.3 ± 2.2 3.7 ± 2.4 2.5 ± 1.4
Cortisol before osilodrostat intake 422.9 ± 159.2 414.7 ± 176.6 439.4 ± 130.7
Cortisol 4 hour after osilodrostat 404 ± 165.6 408.2 ± 200.1 395.5 ± 70.8

 

Abbreviations: CD, Cushing’s disease; ULN, upper limit range; UFC, urinary free cortisol.

aOf note, none of the included patients were Asian.

In their article, Ménard et al.6 showed that the dose–exposure relationship was not strictly proportional. A one-compartment model was enhanced by increasing the relative bioavailability with the dose and was estimated that the dose resulting in a 50% increase in bioavailability was 1.06 mg. The PK parameters derived from Ménard et al.6 were fixed and used to predict osilodrostat concentration in our patients. A direct relationship between the predicted osilodrostat concentrations and variation of cortisol concentrations (%) gave a better fit than an indirect model. The drug effect was modeled with the following sigmoidal function (Eq. 1);

(1)

where Imax is the maximal inhibition and IC50 is the apparent half-maximal inhibitory concentration.

The estimated PD parameters were IC50 and Imax. Their values as well as the relative standard errors (RSE%) and the corresponding bootstrap IC50 are shown in Table 2. Final parameters were used to simulate n = 500 profiles following a single dose of osilodrostat.

 

 

 

Table 2.

Pharmacodynamic parameters of osilodrostat’s effects on the variation of cortisol concentrations.

Parameters Unit Estimation RSE% Bootstrap
0.025 0.975
KA (fixed)a 1/hour 4.03
CL/F (fixed)a L/hour 18.3
V/F (fixed)a L 125
Imax % 44.5 18.7 12.51 90.9
IC50 mg/L 0.011 37.4 0.0001 0.10
Interindividual variability (ω)
 Imax 0.40 30.9 0.003 1.86
 IC50 3.78 41.0 0.003 9.22
Residual unexplained variability (σ)
 Additive % 23.8 12.2 18.2 29.9

 

Abbreviations: CL/F, apparent clearance; IC50, osilodrostat concentration associated with half the maximal inhibition of the cortisol variation; Imax, maximum inhibitory effect of osilodrostat on the variation of cortisol; KA, first-order absorption rate constant; RSE, relative standard error; V/F, apparent volume of distribution.

 

aAdapted from Ménard et al.6

The effects on plasma cortisol variation are depicted in Figure 1. Cortisol concentration declines during the first hour after taking osilodrostat, from 24% for a 1 mg dose to over 42% for a 20 mg dose. Thereafter, from the first hour onward, cortisol increases progressively, with loss of treatment efficacy occurring around the 10th-15th hour for 1 and 2 mg, while for doses above 5 mg, a moderate effect persists over the following hours. Figure 2 shows the variation in cortisol concentration for a 2 mg dose, with median decrease in cortisol variation of 31%, ranging from 0% to 67.5%, with, as mentioned above, a maximum effect 1 hour after osilodrostat intake, and a progressive increase in cortisol levels, mainly during the 12 hours following treatment. The same analysis for 10 mg revealed a median reduction in cortisol of 38%, ranging from 5% to 80%. Figure 3 describes the relationship between osilodrostat concentration and cortisol variation, showing that the maximum effect corresponds to the maximum concentration and that a decrease in osilodrostat concentration results in an increase in cortisol level.

Relationship between time since last administration of osilodrostat and cortisol concentrations.

Figure 1.

Relationship between time since last administration of osilodrostat and cortisol concentrations.

Visual predictive variation on cortisol concentrations following 2 or 10 mg osilodrostat administration.

Figure 2.

Visual predictive variation on cortisol concentrations following 2 or 10 mg osilodrostat administration.

Relation between osilodrostat concentration and cortisol variation.

Figure 3.

Relation between osilodrostat concentration and cortisol variation.

Discussion

To the best of our knowledge, this is the first study that attempts to define a dose/efficacy relationship between osilodrostat dose and the variation of plasma cortisol. First, our results suggest that the effect of osilodrostat appears immediately after the peak of concentration, 1 hour after treatment intake, which highlights the parallel evolution of osilodrostat and cortisol concentrations. This is unusual, as typically effect peak takes few hours, following concentration peak.15 The relationship between osilodrostat concentration and the effect on cortisol is not linear but sigmoidal with a rapid increase in concentrations producing a rapid significant effect, leading to a maximal effect. Because elimination is a slower process than absorption, the effect’s decline will also be slower: this means that efficiency remains stable during the first 5 hours, with a further progressive increase of cortisol and a loss of efficiency around 10-15 hours after intake. This confirms the need for two intakes per day, with one early in the morning and the other 12 hours later in the evening. In addition, even if our simulation suggests a wide interindividual variability, we were able to determine the impact of different doses of osilodrostat on the percent decrease in plasma cortisol levels. For instance, 20 mg osilodrostat leads to an estimated 42% decrease in cortisol concentration. Interestingly, Ferrari et al.16 recently showed that patients controlled with two doses of osilodrostat for at least 1 month had the same efficacy with a single intake (combing both doses) at 4 or 7 Pm. This is quite surprising and will need to be evaluated in future studies: our preliminary model could give more precise information on this point.

Cushing’s syndrome is also characterized by a loss of circadian rhythm leading to increased comorbidities such as diabetes, hypertension, and cardiovascular disease.17,18 This is why 24 hour UFC can only be considered an imperfect marker of glucocorticoid overexposure even though it is an easy-to-use marker, as exemplified by its use in all the clinical trials performed on cortisol-lowering drugs.7,8,10,19 Predicting the efficacy of osilodrostat on plasma cortisol might be helpful to tailor the treatment as a titrating approach. Of note, some studies suggested that there might be an inpatient variability of cortisol secretion in Cushing’s syndrome,20 and this might account for a bias in our results. However, none of our patients had cyclical Cushing’s syndrome. Moreover, 12 patients in our cohort had at least two cortisol cycles (every 4 hours during the day) before starting treatment. A comparison of these two cycles using Student’s t-test showed no significant difference (P = .7), indicating no obvious spontaneous variability. Our preliminary report gives interesting insights into the maximal efficacy expected for a single dose of osilodrostat, thus defining the initial dosage needed to rapidly control hypercortisolism, as opposed to the dose currently recommended by the manufacturer (2 mg twice daily). Thus, our results could help define an optimal dose in the morning, but also in the evening, with the aim of re-establishing a circadian profile. This will, however, have to be confirmed on an interventional study focusing on comorbidities, quality of life and their potential improvements while using this PK model.

The main limitation of this proof-of-concept study is the large CI. This may be due to the relatively low number of patients and the fact that cortisol was measured every 4 hours instead of every hour, but also to the large variability in efficacy between subjects. Due to the number of patients included in the analysis, it was not possible to investigate further if a covariate, such as the gender, may explain these differences between individuals. It is important to highlight that although our model predicts cortisol levels 1 hour post intake as the most reliable predictor of future efficacy, cortisol measurements were taken every 4 hours. Thus, this finding should be confirmed in prospective studies with more frequent cortisol measurements, particularly 1 hour after osilodrostat administration. While the kinetic–pharmacodynamic approach used in this study can present with some inherent limitations, this type of approach is regularly used to define the modalities of use for a medication in a new indication. A nonlinear mixed-effects modeling allows the use of data from the routine clinical follow-up of patients. This method is thus effective and particularly well-suited for sparse data. Finally, a larger study could include closer measurements of cortisol. Liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) is the best method for avoiding cross-reactivity with steroid precursors and could be used for these measurements. However, we used the Elecsys Cortisol II Immunoassay, which shows <5% cross-reactivity with 11-deoxycortisol; thus, our results are credible.

In conclusion, we designed a kinetic–pharmacodynamic model to adapt osilodrostat in patients with ACTH-dependent Cushing’s syndrome. Our model shows that cortisol level 1 hour after treatment is the best indicator of future efficacy. Moreover, depending on the initial cortisol level and the goal to be achieved, different doses should be prescribed. Despite wide inter-patient variability, we believe our model provides insight into the minimal dose necessary to decrease cortisol levels and the maximal efficacy expected for a given dose. Thus, it should help physicians tailor the treatment to reach maximal efficacy in the shortest possible time. The next step will be to analyze whether this percent decrease remains stable on a long-term basis or becomes more important with time, as suggested by some clinical cases showing delayed adrenal insufficiency on stable doses of osilodrostat.21

Authors’ contributions

Cecilia Piazzola (Conceptualization [equal], Formal analysis [equal], Writing—original draft [equal]), Frederic Castinetti (Conceptualization [equal], Formal analysis [equal], Writing—review & editing [equal]), Katharina von Fabeck (Conceptualization [equal], Writing—review & editing [equal]), and Nicolas Simon (Conceptualization [equal], Methodology [equal], Supervision [equal], Validation [equal], Writing—original draft [equal], Writing—review & editing [equal])

Funding

This work received an unrestricted educational grant from Recordati Rare Diseases.

To see the references and the original article, please go here: https://academic.oup.com/ejendo/article/193/4/K11/8255719?login=false